global-journal-of-computer-science-and-technology-f-graphics-vision Global Journal of Computer Science and Technology - F: Graphics & Vision 0975-4350 0975-4172 Global Journals Publishing Group Incorporated 75934 Performance Evaluation of SVM a RBF Kernel for Medical Image Classification N.T.Renukadevi INDIA, Kongu Engineering College 15 01 2013 13 4 15 19

An approach for automatic classification of computed tomography (CT) medical images is presented in this paper. A vast amount of CT images are produced in modern hospitals due to advances of multi-slice Computed Tomography (CT) Scan which handles up to 64 slices per scan. So, an input image based automatic medical image retrieval system is now a necessity. In this paper, Coiflet wavelets are used to extract feature from the CT images. The extracted features are then classified using Support Vector Machine (SVM) with Radial Basis Function (RBF). The performance of SVM for varying parameters is investigated.

 content based image retrieval (CBIR) computed tomography (CT) coiflet wavelets support vector machine (SVM) radial basis function (RBF). Full Text

An approach for automatic classification of computed tomography (CT) medical images is presented in this paper. A vast amount of CT images are produced in modern hospitals due to advances of multi-slice Computed Tomography (CT) Scan which handles up to 64 slices per scan. So, an input image based automatic medical image retrieval system is now a necessity. In this paper, Coiflet wavelets are used to extract feature from the CT images. The extracted features are then classified using Support Vector Machine (SVM) with Radial Basis Function (RBF). The performance of SVM for varying parameters is investigated.